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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Paper illustration for Argument Mapping
Decision Making
Argument Mapping
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.When statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
HighHighMediumLow
Timedifferent
1-4 Wochen1 Tag bis mehrere Wochen1-3 h1-5 Tage
Participantsdifferent
1-64-101-8Nutzertraffic
Formatdifferent
AsyncWorkshopWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryProblem Statement, Prototype, Test LearningsArgument Map, Evidence Gaps, Decision RationaleInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
InnovationPrototypeResearch
SensemakingDecisionRationale
ValidationExperimentsDemandGrowth
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